端到端的终结：一项视频理解五项全能挑战（2020）
计算机视觉与模式识别
2020-08-04 v1
摘要
我们提出一项新的视频理解五项全能挑战，这是与 IEEE 计算机视觉与模式识别会议（CVPR）2020 联合举办的开放竞赛。该挑战的目标是探索并评估用于文本到视频检索——即使用自然语言查询在视频语料库中搜索内容——的新方法。本报告总结了该挑战首版的结果及参与者的发现。
引用
@article{arxiv.2008.00744,
title = {The End-of-End-to-End: A Video Understanding Pentathlon Challenge (2020)},
author = {Samuel Albanie and Yang Liu and Arsha Nagrani and Antoine Miech and Ernesto Coto and Ivan Laptev and Rahul Sukthankar and Bernard Ghanem and Andrew Zisserman and Valentin Gabeur and Chen Sun and Karteek Alahari and Cordelia Schmid and Shizhe Chen and Yida Zhao and Qin Jin and Kaixu Cui and Hui Liu and Chen Wang and Yudong Jiang and Xiaoshuai Hao},
journal= {arXiv preprint arXiv:2008.00744},
year = {2020}
}
备注
Individual reports, dataset information, rules, and released source code can be found at the competition webpage (https://www.robots.ox.ac.uk/~vgg/challenges/video-pentathlon)